
Apache Superset
modern, enterprise-ready business intelligence web application
What is Apache Superset?
Apache Superset is a data exploration and visualization web application.
Superset provides:
- An intuitive interface to explore and visualize datasets, and create interactive dashboards.
- A wide array of beautiful visualizations to showcase your data.
- Easy, code-free, user flows to drill down and slice and dice the data underlying exposed dashboards. The dashboards and charts acts as a starting point for deeper analysis.
- A state of the art SQL editor/IDE exposing a rich metadata browser, and an easy workflow to create visualizations out of any result set.
- An extensible, high granularity security model allowing intricate rules on who can access which product features and datasets. Integration with major authentication backends (database, OpenID, LDAP, OAuth, REMOTE_USER, ...)
- A lightweight semantic layer, allowing to control how data sources are exposed to the user by defining dimensions and metrics
- Out of the box support for most SQL-speaking databases
- Deep integration with Druid allows for Superset to stay blazing fast while slicing and dicing large, realtime datasets
- Fast loading dashboards with configurable caching
Apache Superset Screenshots










Apache Superset Features
Apache Superset information
Supported Languages
- English
GitHub repository
- 52,147 Stars
- 10,658 Forks
- 1352 Open Issues
- Updated
Comments and Reviews
Tags
- Data Analysis
- analytics
- Web Analytics
- business-analytics-dashboard
- business-analytics
- Business Intelligence
Category
Network & AdminRecent user activities on Apache Superset
atomicWeb added Apache Superset as alternative(s) to RootDB
- YanzuFounder liked Apache SupersetYa
Jpy added Apache Superset as alternative(s) to Datami
The big problem with this very beautiful tool is that every chart can be represented in the true end by only a single query, so you CANNOT take data from more than one single dataset for chart, until you write off a custom virtual dataset with the data you need.
But the critical example where you have a single chart with two lines, one from a 600k lines table with a time-serie and a second one from a 200M with a different time-serie, you need to """merge""" them together as a single dataset, with a lot of heavy lifting with absolutely no reason to be.